7 자유도 로봇 매니퓰레이터의 전역성능 향상을 위한 기구 최적설계

Abstract

This paper presents the procedure and results of the multi-objective design optimization of a seven-degrees-of-freedom (7 DOF) robot manipulator for better global performance, which pertains to the Global Conditioning Index (GCI), Global Manipulability Index (GMI), and the Structural Length Index (SLI). The concepts of, and the calculation techniques for, GCI,GMI, and SLI are introduced to allow their use as objective functions for optimization. As the first optimization technique, the Grey-based Taguchi method was used. The Taguchi method was used to reduce the time needed to analyze the global performance of the robot manipulator. Grey relational analysis was performed to deal with the multiple performances of the manipulator by converting multiple responses into a single response with a Grey relational grade. The second optimization techniques, which are the Micro Genetic Algorithm (μGA), and Evolutionary Algorithm (EA), Progressive Quadratic Response Surface Method (PQRSM), Sequential Two-point Diagonal Quadratic Approximate Optimization (STDQAO), were explained briefly, and they are being used to optimize the global performance indices based on approximate model of the robot manipulator. Analysis of variance (ANOVA) was done to analyze the effect of the link parameters on the performance of the robot manipulator, and to determine which link parameter affects the performance of the robot manipulator. The results of the optimization of the prototype robot manipulator and the comparison of the optimization results with those optimization techniques are presented herein.